System and method for assigning requests in a content distribution network

ABSTRACT

A system includes a plurality of edge routers and a route controller. The edge routers are configured to direct requests from a client system to one of a plurality of cache servers. Each of the cache servers is configured to provide content to the client system in response to the requests. The route controller is configured to receive demand information from the edge routers, estimate an optimal request distribution based on the demand information using a bicriteria approximation algorithm, and provide each of the edge routers with route information.

FIELD OF THE DISCLOSURE

The present disclosure generally relates to communications networks, andmore particularly relates to assigning requests in a ContentDistribution Network (CDN).

BACKGROUND

Packet-switched networks, such as networks based on the TCP/IP protocolsuite, can distribute a rich array of digital content to a variety ofclient applications. One popular application is a personal computerbrowser for retrieving documents over the Internet written in theHypertext Markup Language (HTML,). Frequently, these documents includeembedded content. Where once the digital content consisted primarily oftext and static images, digital content has grown to include audio andvideo content as well as dynamic content customized for an individualuser.

It is often advantageous when distributing digital content across apacket-switched network to divide the duty of answering content requestsamong a plurality of geographically dispersed servers. For example,popular Web sites on the Internet often provide links to “mirror” sitesthat replicate original content at a number of geographically dispersedlocations. A more recent alternative to mirroring is contentdistribution networks (CDNs) that dynamically redirect content requeststo a cache server situated closer to the client issuing the request.CDNs either co-locate cache servers within Internet Service Providers ordeploy them within their own separate networks.

BRIEF DESCRIPTION OF THE DRAWINGS

It will be appreciated that for simplicity and clarity of illustration,elements illustrated in the Figures have not necessarily been drawn toscale. For example, the dimensions of some of the elements areexaggerated relative to other elements. Embodiments incorporatingteachings of the present disclosure are shown and described with respectto the drawings presented herein, in which:

FIG. 1 is a diagram illustrating a communications network in accordancewith one embodiment of the present disclosure;

FIG. 2 is a diagram illustrating a CDN in accordance with one embodimentof the present disclosure;

FIGS. 3-5 are flow diagrams illustrating exemplary methods of allocatingrequests between cache servers in accordance with embodiments of thepresent disclosure; and

FIG. 6 is an illustrative embodiment of a general computer system.

The use of the same reference symbols in different drawings indicatessimilar or identical items.

DETAILED DESCRIPTION OF THE DRAWINGS

The numerous innovative teachings of the present application will bedescribed with particular reference to the presently preferred exemplaryembodiments. However, it should be understood that this class ofembodiments provides only a few examples of the many advantageous usesof the innovative teachings herein. In general, statements made in thespecification of the present application do not necessarily limit any ofthe various claimed inventions. Moreover, some statements may apply tosome inventive features but not to others.

FIG. 1 shows a geographically dispersed network 100, such as theInternet. Network 100 can include routers 102, 104, and 106 thatcommunicate with each other and form an autonomous system (AS) 108. AS108 can connect to other ASs that form network 100 through peeringpoints at routers 102 and 104. Additionally, AS 108 can include clientsystems 110, 112, 114, and 116 connected to respective routers 102, 104,and 106 to access the network 100. Router 102 can provide ingress andegress for client system 110. Similarly, router 104 can provide ingressand egress for client system 112. Router 106 can provide ingress andegress for both of client systems 114 and 116.

AS 108 can further include a Domain Name System (DNS) server 118. DNSserver 118 can translate a human readable hostname, such as www.att.com,into an Internet Protocol (IP) address. For example, client system 110can send a request to resolve a hostname to DNS server 118. DNS server118 can provide client system 110 with an IP address corresponding tothe hostname. DNS server 118 may provide the IP address from a cache ofhostname-IP address pairs or may request the IP address corresponding tothe hostname from an authoritative DNS server for the domain to whichthe hostname belongs.

Client systems 110, 112, 114, and 116 can retrieve information from aserver 120. For example, client system 112 can retrieve a web pageprovided by server 120. Additionally, client system 112 may downloadcontent files, such as graphic, audio, and video content, and programfiles such as software updates, from server 120. The time required forclient system 112 to retrieve the information from the server 120normally is related to the size of the file, the distance theinformation travels, and congestion along the route. Additionally, theload on the server 120 is related to the number of client systems 110,112, 114, and 116 that are actively retrieving information from theserver 120. As such, the resources such as processor, memory, andbandwidth available to the server 120 limit the number of client systems110, 112, 114, and 116 that can simultaneously retrieve information fromthe server 120.

Additionally, the network can include cache servers 122 and 124replicating content on the server 120 that can be located more closelywithin the network to the client systems 110, 112, 114, and 116. Cacheserver 122 can link to router 102, and cache server 124 can link torouter 106. Client systems 110, 112, 114, and 116 can be assigned cacheserver 122 or 124 to decrease the time needed to retrieve information,such as by selecting the cache server closer to the particular clientsystem. The network distance between a cache server and client systemcan be determined by network cost and access time. As such, theeffective network distance between the cache server and the clientsystem may be different from the geographic distance.

When assigning cache servers 122 and 124 to client systems 110 through116, the cache server closest to the client can be selected. The closestcache server may be the cache server having a shortest network distance,a lowest network cost, a lowest network latency, a highest linkcapacity, or any combination thereof. Client system 110 can be assignedcache server 122, and client systems 114 and 116 can be assigned tocache server 124. The network costs of assigning client system 112 toeither of cache server 122 or 124 may be substantially identical. Whenthe network costs associated with the link between router 102 and router104 are marginally lower than the network costs associated with the linkbetween router 104 and router 106, client 112 may be assigned to cacheserver 124.

Client system 112 may send a request for information to cache server124. If cache server 124 has the information stored in a cache, it canprovide the information to client system 112. This can decrease thedistance the information travels and reduce the time to retrieve theinformation. Alternatively, when cache server 124 does not have theinformation, it can retrieve the information from server 120 prior toproviding the information to the client system 112. In an embodiment,cache server 124 may attempt to retrieve the information from cacheserver 122 prior to retrieving the information from server 120. Thecache server 124 may retrieve the information from the server 120 onlyonce, reducing the load on server 120 and network 100 such as, forexample, when client system 114 requests the same information.

Cache server 124 can have a cache of a limited size. The addition of newcontent to the cache may require old content to be removed from thecache. The cache may utilize a least recently used (LRU) policy, a leastfrequently used (LFU) policy, or another cache policy known in the art.When the addition of relatively cold or less popular content to thecache causes relatively hot or more popular content to be removed fromthe cache, an additional request for the relatively hot content canincrease the time required to provide the relatively hot content to theclient system, such as client system 114. To maximize the cost savingsand time savings of providing content from the cache, the most popularcontent may be stored in the cache, while less popular content isretrieved from server 120.

FIG. 2 illustrates an anycast CDN system 200 that can be used inconjunction with communications network 100. The anycast CDN system 200can include a CDN provider network 202. The CDN provider network 202 caninclude a plurality of provider edge routers 204 through 214. Theprovider edge routers 204 through 214 can serve as ingress points fortraffic destined for the CDN provider network 202, and egress points fortraffic from the CDN provider network 202 destined for the rest of theInternet. The anycast CDN system 200 can further include cache servers216 and 218. Cache server 216 can receive traffic from the CDN providernetwork 202 through provider edge router 204, and cache server 218 canreceive traffic from the CDN provider network 202 through edge cacherouter 214. In addition to providing CDN service to clients within theCDN provider network, the anycast CDN system 200 can provide CDN serviceto clients within AS 220 and AS 222. AS 220 can include provider edgerouters 224 and 226 with peering connections to provider edge routers206 and 208, respectively. Similarly, AS 222 can include provider edgerouters 228 and 230 with peering connections to provider edge routers210 and 212 respectively. Requests for content from systems withineither AS 220 or AS 222 may enter the CDN provider network through theappropriate peering points and be directed to either cache server 216 or218.

Each of provider edge routers 206 through 212 contributes an amount ofrequests per unit time. One cache server, such as cache server 216,should serve all the requests from one of the provider edge routers,such as provider edge router 206, due to the underlying IP anycastrouting architecture. Additionally, there is a connection costassociated with serving requests from a provider edge router at a cacheserver. The connection cost is typically proportional to the distancebetween the cache server and the provider edge router. Generally, it isdesirable to serve the requests from a provider edge router at theclosest cache server. Additionally, there is a setup cost associatedwith serving each request. The setup cost can include the processor timeinvolved in processing the request, the time required to retrievecontent that is not cached, and the like. Further, each cache server hasa server capacity for serving requests. The server capacity can berelated to a processor capacity, an amount of memory, an availablenetwork bandwidth, or any combination thereof. Exceeding the servercapacity can be particularly undesirable. Exceeding the server capacityof a cache server can impact the response time for a significant numberof requests being served by the cache server. Accordingly, it can bedesirable to serve requests from a cache server further from theprovider edge router in order to avoid exceeding the server capacity ofthe closest cache server.

Anycast CDN system 200 can also include a route controller 232. Theroute controller 232 can exchange routes with provider edge routers 206through 212 within the CDN provider network 202. As such, the routecontroller 232 can influence the routes selected by the provider edgerouters 206 through 212. Additionally, the route controller 232 canreceive load information from cache servers 216 and 218.

Cache servers 216 and 218 can advertise, such as through Border GatewayProtocol (BGP), a shared anycast address to the CDN provider network202, specifically to provider edge routers 204 and 214. Provider edgerouters 204 and 214 can advertise the anycast address to the routecontroller 232. The route controller 232 can provide a route to theanycast address to each of the provider edge routers 206 though 212.Provider edge routers 206 through 212 can direct traffic addressed tothe anycast address to either of the cache servers 216 and 218 based onthe routes provided by the route controller 232. Additionally, theprovider edge routers 206 through 212 can advertise the anycast addressto AS 220 and AS 222. The route controller 232 can manipulate the routeprovided to provider edge routers 206 through 212 based on the load onthe cache servers 216 and 218, network bandwidth, network cost, networkdistance, or any combination thereof. Altering the route to the anycastaddress can change which of cache servers 216 and 218 serve content toclient systems within the CDN provider network 202, AS 220, and AS 222.

In an embodiment, AS 220 may be an unstable network. Traffic from clientsystems within the AS 220 may enter the CDN provider network 202 at bothprovider edge routers 206 and 208. When anycast traffic from the sameclient system enters the CDN provider network 202 at both provider edgerouters 206 and 208, portions of the traffic may be directed todifferent cache servers 216 and 218. Persistent and/or secureconnections may be disrupted when portions of the traffic are sent todifferent cache servers 216 and 218. As such, it is undesirable toprovide an anycast address to client systems within an unstable network.

FIG. 3 illustrates an exemplary method of optimizing requestdistribution for a CDN network, such as CDN network 200. At 302, arequest distribution system, such as route controller 232, can obtainingress traffic information from a plurality of edge routers, such asedge routers 206 through 212. The ingress traffic information caninclude information about requests sent to cache servers, such as cacheserver 218. At 304, the request distribution system can receive serverload information from the cache servers. The server load information caninclude processor utilization, memory utilization, a number of requestsbeing processed, server capacity, bandwidth utilization, and the like.

In an embodiment, the edge routers can also provide outbound trafficinformation, including the number of responses and the bandwidthutilization of the responses. The outbound traffic information can beused in an estimate of the server capacity required to service theincoming requests.

At 306, the request distribution system can calculate an optimaldistribution of the requests. The optimal distribution of requests canminimize the cost of providing content from the CDN. The cost mayinclude server cost, network cost, time to first byte of the content,time to deliver the content, and the like. Additionally, the optimaldistribution of requests may reduce the likelihood of overloading anyone of the cache servers. At 308, the request distribution system canassign a cache server to each of the edge routers. In an embodiment, acache server can be assigned to more than one edge router. At 310, therequest distribution system can provide each edge router with a routefor a CDN anycast address. The route can deliver the requests associatedwith an edge router to the assigned cache server.

In an alternate embodiment, the request distribution system may obtainingress information based on the distribution of DNS requests for an IPaddress of a cache server and information regarding the server capacityrequired to service the content requests associated with each DNSrequest. For example, a DNS request for a cache server can come from anInternet Service Provider (ISP) DNS server. Information about the numberof content requests and the server capacity required to service thosecontent requests can indicate the amount of server capacity that can berequired to service requests associated with the ISP DNS server.Further, the request distribution system may use optimal distribution ofrequests to assign each DNS request to one or more cache servers.

FIG. 4 illustrates an exemplary method of using a bicriteria (α,β)-approximation algorithm for optimizing request distribution for a CDNnetwork. The bicriteria (α, β)-approximation algorithm can be apolynomial time algorithm that produces a solution having a cost of atmost α times the optimum while violating the capacities by not more thana factor of β. For example, the cost may be at most log n times theoptimum and the capacities can be exceeded by not more than ε times thecapacity, where n is the number of edge routers and ε is a smallfraction.

In an embodiment, the server capacities of all the cache servers can besubstantially similar and can be approximated by a single value S. Forexample, the bandwidth available to each cache server can be the same.Each cache server can exceed the server capacity S by not greater thanSε. In practice, the server capacities S can be defined such that thetrue server capacity is S(1+ε), so that an edge server does not becomeoverloaded. It can be desirable for ε to remain small, such that theover provisioning of each cache server can be small. For example, ε canbe not greater than 0.1, such as not greater than 0.05, or even notgreater than 0.01.

At 402, a request distribution system can receive demand informationfrom the edge routers. In a particular case, all the edge routers canhave demands that are larger than εS. In this case, a cache servershould not be assigned to more than 1/ε edge routers. As such, ε shouldbe less than the number of cache servers divided by the number of edgerouters.

In a more general case, edge routers can have a small demand, such asbetween εS and εS/n, such that n small edge routers can be assigned to aparticulate cache server. Treating the small edge routers separatelyincreases the number of choices, making the running time exponential.Accordingly, during the assignment of the cache servers to the edgerouters, edge routers with a small demand can be combined to create avirtual edge router with a large demand. There may be multiple virtualedge routers formed from different sets of edge routers with smalldemands. Additionally, other edge routers may have a tiny demand, lessthan εS/n. These edge routers may be assigned to the closest cacheserver, as the demand may be assumed to be too small to significantlyviolate the capacity constraint, even when assigned to a fully utilizedcache server.

At 404, the request distribution system can generate a tree with theedge routers and the cache servers as leaves. In an embodiment, thegeneral metrics can be probabilistically embedded into tree metricsresulting in a O(log n) approximation algorithm for general metrics. Forexample, this can be accomplished using the method of Bartal(Proceedings of the 30^(th) Annual ACM Symposium on Theory of Computing,pages 161-168, 1998, the disclosure of which is incorporated herein byreference) or Fakcharoenphol et al. (J. Comput. Syst. Sci., 69(3), pages485-497, 2004, the disclosure of which is incorporated herein byreference). The binary tree can further include a root node, and anumber of intermediate nodes that are root nodes of a subtree. A partialsolution can be determined for a particular subtree rooted at anintermediate node. In a partial solution, not all edge routers of thesubstree may be handled within the subtree and their demands can beoutsourced to another subtree. Similarly, not all cache servers may befully utilized within a subtree and may offer their capacity to edgerouters outside of the subtree. The complete solution at the root nodecan be required to have no outsourced demands.

At 406, the demand for each edge router can be rounded. For example,edge routers with large demands, at least εS, can be rounded down to theclosest multiple of ε²S. This results in a polynomial number of demandsizes as required for a polynomial time algorithm. Edge routers withsmall demands, between εS/n and εS, can be rounded down to the closestmultiple of ε²S/n, such that the small demands can be combined into alarge demand.

At 408, the dynamic programming states can be initialized. For anintermediate or root node, a dynamic programming state can be specifiedby (u, F, D, F_(s), D_(s), F_(exp), F_(imp)), where u is the currentnode, F is a vector representing the available facilities for largecapacities, D is a vector representing the outsourced, or unsatisfied,large clients, F_(s) is the amount of the cache server capacitiesoffered to small clients (a multiple of ε²S/n), D_(s) is the totaldemand of outsourced small clients (a multiple of ε²S/n), F_(exp) is theindex of the cache server being exported from this subtree, and F_(imp)is the index of a cache server of another subtree that is beingutilized. F_(exp) and F_(imp) can take the value “NONE”. For leavesrepresenting edge routers, the initial state is (v, 0, D, 0, D_(s),“NONE”, “NONE”) and the cost can be set to zero if the demand isrepresented in D or D_(s). For leaves representing the cache servers,the initial state is (v, 0, 0, 0, 0, “NONE”, “NONE”). For any F andF_(s) such that the total of F and F_(s), Total(F, F_(s)) is greaterthan zero and not greater than S, that is 0<Total(F, F_(s))≦S, the costcan be the setup cost F₁ of the cache server.

At 410, the assignments of cache servers to edge routers can berecursively determined. For example, the values of the nodes can beupdated from the leaves towards the root. The cost at a node can be thecost of the dynamic programming state plus the cost of moving outsourcedclients in D and D_(s) and the offered facilities in F and F_(s) to thenext higher node. When the state of the child nodes is consistent, theparent node can be the sum of the child nodes if the sum is better thanthe current state, that is when the sum of the costs of the children isbetter than the current lowest cost for the parent.

In an embodiment, the child nodes are consistent when several criteriaare met. First, the sum of the available facilities for large demands ofthe child nodes should be less than the sum of the large demands of thechild nodes. That is, F₁+F₂−F=D₁+D₂−D≧0 where F₁ and F₂ are theavailable capacities of the children for large demands, F is theavailable capacity of the parent for large demands, D₁ and D₂ are theoutsourced demands of the children for large demands, and D isoutsourced demand of the parent for large demands. Additionally, the sunof the available facilities for small demands of the child nodes shouldbe less than the sum of the small demands of the child nodes. That is,F_(s1)+F_(s2)−F_(s)=D_(s1)+D_(s2)−D_(s)≧0, where F_(s1) and F_(s2) arethe available capacities of the children for small demands, F_(s) is theavailable capacity of the parent for small demands, D_(s1) and D_(s2)are the outsourced demands of the children for small demands, and D_(s)is outsourced demand of the parent for small demands. These first twoconditions can ensure that the demand ignored at the parent is actuallymatched to facilities of the same size.

Further, only one exported node F_(exp) and one imported node F_(imp)from the child subtrees should be outside of the parent subtree. Forexample, if a first child does not have an exported node(F_(exp)=“NONE”) and the second child has an exported node, then theparent would have the exported node of the second child. In anotherexample, if the imported node from the first child is the same as theexported node of the second child, then the parent can import theimported node of the second child because the imported node of the firstchild is within the subtree of the parent. Specifically, y₁=x₂ or y₁=yor y₁=“NONE”, and y₂=x₁ or y₂=y or y₂=“NONE”, where x₁ and x₂ are theindices of the exported facilities for the children, y₁ and y₂ are theindices of the imported facilities for the children, and y is the indexfor the imported facility for the parent. The two conditions can ensurethat what is requested by a subtree is provided for or put on therequest list of the parent. Additionally, x=x₁ or x=x₂ or x=“NONE”,where x is the index for the exported facility for the parent. Thiscondition can prevent the parent from exporting a facility that is notavailable. Once the states have been updated and the root node has aconsistent low cost state that satisfies all the demands of the edgerouters, then the assignments can be determined recursively from theroot node.

At 412, fractional assignments can be adjusted. Due to the grouping ofthe small demands, a small demand from an edge router could be assignedto multiple cache servers. To accommodate the underlying anycastarchitecture, a single cache server should handle the demand from anysingle edge router. Any fractional assignments of small demands can beadjusted accordingly. This can be done, for example, using the algorithmof Shmoys and Tardos (Math. Programming, 62(3, Ser. A), pages 461-474,1993, the disclosure of which is incorporated herein by reference).

At 414, the request distribution system can provide the routeinformation to the edge routers. From the assignments of the cacheservers to the edge routers, the system can determine routes from eachedge router to the assigned cache server. The topology of the network,including locations of any internal routers, can be incorporated intothe routes so that routes to different cache servers do not cross thesame internal router. The route information, including the next hop forpackets to the anycast address of the cache servers, can be sent to eachof the edge routers and internal routers. The system can return to 402to receive additional demand information from the edge routers.

FIG. 5 illustrates another exemplary method of using a bicriteria (α,β)-approximation algorithm for optimizing request distribution for a CDNnetwork. In an embodiment, the server capacities of all the cacheservers may not be the same. For example, the cache servers may havedifferent processor capacities, different amounts of memory, ordifferent available bandwidths. In this case, the identification ofsmall demands can be relative to the server to which the demand isassigned. As small demands and large demands were treated separately inthe previously described uniform capacity case, accommodating thechanges in the type of demand for the edge router based on the assignedcache server can result in a non-polynomial algorithm. However, when alldemands are treated as either large demands (significant demands to beallocated) or tiny demands (insignificant demands that can be assignedto the closest cache server), a polynomial time algorithm can beachieved.

At 502, a request distribution system can receive demand informationfrom edge routers and capacity information from cache servers. At 504,the request distribution system can generate a binary tree with the edgerouters and the cache servers as leaves. At 506, the demand from eachedge router can be rounded, and at 508, the capacity of each cacheserver can be rounded. For example, the demand can be rounded down tothe closest (1+ε)^(k) and the capacities can be rounded up to theclosest (1+ε)^(k), where k is an integer. This results in a polynomialnumber of capacity sizes and demand sizes, as required for thepolynomial time algorithm.

At 510, the dynamic programming states can be initialized. Because thereare no small demands, the dynamic programming state can be specified by(u, base, F, D), where u is the current node, base is the largestcapacity or demand in F or D, F is a vector of logarithmic lengthrepresenting the available facilities of different sizes, and D is avector of logarithmic length representing the outsourced, orunsatisfied, edge routers of different sizes. The span of F and D can bea multiplicative range of ε/n and having a length of log_(1+ε)(n/ε).Additionally, unless F=D=0, one of them has a nonzero value in its mostsignification entry and can be stored in a normalized fashion. At 512,the assignments of cache servers to edge routers can be recursivelydetermined. At 514, the request distribution system can provide theroute information to the edge routers. The system can return to 502 toreceive additional information from the edge routers and cache servers.

FIG. 6 shows an illustrative embodiment of a general computer system600. The computer system 600 can include a set of instructions that canbe executed to cause the computer system to perform any one or more ofthe methods or computer based functions disclosed herein. The computersystem 600 may operate as a standalone device or may be connected, suchas by using a network, to other computer systems or peripheral devices.

In a networked deployment, the computer system may operate in thecapacity of a server or as a client user computer in a server-clientuser network environment, or as a peer computer system in a peer-to-peer(or distributed) network environment. The computer system 600 can alsobe implemented as or incorporated into various devices, such as apersonal computer (PC), a tablet PC, an STB, a personal digitalassistant (PDA), a mobile device, a palmtop computer, a laptop computer,a desktop computer, a communications device, a wireless telephone, aland-line telephone, a control system, a camera, a scanner, a facsimilemachine, a printer, a pager, a personal trusted device, a web appliance,a network router, switch or bridge, or any other machine capable ofexecuting a set of instructions (sequential or otherwise) that specifyactions to be taken by that machine. In a particular embodiment, thecomputer system 600 can be implemented using electronic devices thatprovide voice, video or data communication. Further, while a singlecomputer system 600 is illustrated, the term “system” shall also betaken to include any collection of systems or sub-systems thatindividually or jointly execute a set, or multiple sets, of instructionsto perform one or more computer functions.

The computer system 600 may include a processor 602, such as a centralprocessing unit (CPU), a graphics processing unit (GPU), or both.Moreover, the computer system 600 can include a main memory 604 and astatic memory 606 that can communicate with each other via a bus 608. Asshown, the computer system 600 may further include a video display unit610 such as a liquid crystal display (LCD), an organic light emittingdiode (OLED), a flat panel display, a solid-state display, or a cathoderay tube (CRT). Additionally, the computer system 600 may include aninput device 612 such as a keyboard, and a cursor control device 614such as a mouse. Alternatively, input device 612 and cursor controldevice 614 can be combined in a touchpad or touch sensitive screen. Thecomputer system 600 can also include a disk drive unit 616, a signalgeneration device 618 such as a speaker or remote control, and a networkinterface device 620 to communicate with a network 626. In a particularembodiment, the disk drive unit 616 may include a computer-readablemedium 622 in which one or more sets of instructions 624, such assoftware, can be embedded. Further, the instructions 624 may embody oneor more of the methods or logic as described herein. In a particularembodiment, the instructions 624 may reside completely, or at leastpartially, within the main memory 604, the static memory 606, and/orwithin the processor 602 during execution by the computer system 600.The main memory 604 and the processor 602 also may includecomputer-readable media.

The illustrations of the embodiments described herein are intended toprovide a general understanding of the structure of the variousembodiments. The illustrations are not intended to serve as a completedescription of all of the elements and features of apparatus and systemsthat utilize the structures or methods described herein. Many otherembodiments may be apparent to those of skill in the art upon reviewingthe disclosure. Other embodiments may be utilized and derived from thedisclosure, such that structural and logical substitutions and changesmay be made without departing from the scope of the disclosure.Additionally, the illustrations are merely representational and may notbe drawn to scale. Certain proportions within the illustrations may beexaggerated, while other proportions may be minimized. Accordingly, thedisclosure and the FIGs. are to be regarded as illustrative rather thanrestrictive.

The Abstract of the Disclosure is provided to comply with 37 C.F.R.§1.72(b) and is submitted with the understanding that it will not beused to interpret or limit the scope or meaning of the claims. Inaddition, in the foregoing Detailed Description of the Drawings, variousfeatures may be grouped together or described in a single embodiment forthe purpose of streamlining the disclosure. This disclosure is not to beinterpreted as reflecting an intention that the claimed embodimentsrequire more features than are expressly recited in each claim. Rather,as the following claims reflect, inventive subject matter may bedirected to less than all of the features of any of the disclosedembodiments. Thus, the following claims are incorporated into theDetailed Description of the Drawings, with each claim standing on itsown as defining separately claimed subject matter.

The above disclosed subject matter is to be considered illustrative, andnot restrictive, and the appended claims are intended to cover all suchmodifications, enhancements, and other embodiments which fall within thetrue spirit and scope of the present disclosed subject matter. Thus, tothe maximum extent allowed by law, the scope of the present disclosedsubject matter is to be determined by the broadest permissibleinterpretation of the following claims and their equivalents, and shallnot be restricted or limited by the foregoing detailed description.

1. A system comprising: a plurality of edge routers configured to directrequests from a client system to one of a plurality of cache servers,each of the cache servers configured to provide content to the clientsystem in response to the requests; and a route controller comprising aprocessor configured to: receive demand information from the edgerouters; estimate an optimal request distribution based on the demandinformation using a bicriteria approximation algorithm, wherein initialprogramming states for the estimation are specified by (u, F, D, F_(S),D_(S), F_(exp), Fimp), where u is a current node, F is a vectorrepresenting an available facility for large capacity, D is a vectorrepresenting an outsourced large client, F_(S) is an amount of cacheserver capacity offered to small clients, D_(S) is a total demand ofoutsourced small clients, F_(exp) is an index of a cache server beingexported from a subtree, and F_(imp) is an index of another cache serverof another subtree that is being utilized; and provide each of the edgerouters with anycast route information for the cache servers.
 2. Thesystem of claim 1, wherein the demand information includes a number ofrequests per unit time.
 3. The system of claim 1, wherein each of theplurality of cache servers has a server capacity.
 4. The system of claim3, wherein the route controller is further configured to receive servercapacity information from the plurality of cache servers.
 5. The systemof claim 4, wherein the optimal request distribution is further based onthe server capacity information.
 6. A route controller comprising: aprocessor configured to: receive demand information from a plurality ofedge routers; divide the edge routers into edge routers with largedemands and edge routers with small demands; combine a number of edgerouters with small demands into a virtual large demand router; usedynamic programming to recursively assign each cache server to an edgerouter; determine route information based on the edge router assigned toeach cache server; and provide each of the edge routers with routeinformation for the assigned cache servers.
 7. The route controller ofclaim 6, wherein the demand information includes a number of requestsper unit time.
 8. The route controller of claim 6, wherein the processoris further configured to receive server capacity information from theplurality of cache servers.
 9. The route controller of claim 8, whereinthe optimal request distribution is further based on the server capacityinformation.
 10. A system comprising a processor and a non-transitorycomputer readable medium comprising a plurality of instructions tomanipulate the processor, the plurality of instructions comprising:instructions to receive demand information from a plurality of edgerouters; instructions to divide the edge routers into edge routers withlarge demands and edge routers with small demands; instructions tocombine a number of edge routers with small demands into a virtual largedemand router; instructions to use dynamic programming to recursivelyassign each cache server to an edge router; instructions to determineroute information based on the edge router assigned to each cacheserver; and instructions to provide each of the edge routers with routeinformation for the assigned cache servers.
 11. The system of claim 10,wherein the demand information includes a number of requests per unittime.
 12. The system of claim 10, wherein the plurality of instructionsfurther comprises instructions to receive server load information from aplurality of cache servers.
 13. The system of claim 12, wherein thedistribution of requests is further based on the server capacityinformation.
 14. A system comprising: a plurality of edge routersconfigured to direct requests from a client system to one of a pluralityof cache servers, each of the cache servers configured to providecontent to the client system in response to the requests; and a routecontroller comprising a processor configured to: receive demandinformation from the edge routers; divide the edge routers into edgerouters with large demands and edge routers with small demands; combinea number of edge routers with small demands into a virtual large demandrouter; use dynamic programming to recursively assign each cache serverto an edge router; determine route information based on the edge routerassigned to each cache server; and provide each of the edge routers withroute information.
 15. The system of claim 14, wherein the demandinformation includes a number of requests per unit time.